Large Language Models in Bioinformatics: A Survey

Large Language Models (LLMs) are revolutionizing bioinformatics, enabling advanced analysis of DNA, RNA, proteins, and single-cell data.This survey provides a systematic review of recent advancements, focusing on genomic sequence modeling, RNA structure prediction, protein function inference, and single-cell transcriptomics.Meanwhile, we also discuss several key challenges, including data scarcity, computational complexity, and cross-omics integration, and explore future directions such as multimodal learning, hybrid AI models, and clinical applications.By offering a comprehensive perspective, this paper underscores the transformative potential of LLMs in driving innovations in bioinformatics and precision medicine.

Authors

Publication Details

Published
2025-01-01
DOI
https://doi.org/10.18653/v1/2025.findings-acl.184
Citations
4
Primary Topic
Genetics, Bioinformatics, and Biomedical Research
Type
article
Field-Weighted Citation Impact
3.22

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article

Large Language Models in Bioinformatics: A Survey

Jianmin Jiang, Yu Li, Pengan Chen, Zikang Wang et al.
4 citations
Genetics, Bioinformatics, and Biomedical Research
3.22
article

Large Language Models in Bioinformatics: A Survey

Jianmin Jiang, Yu Li, Pengan Chen, Zikang Wang, Zhenyu Wang, Xiangyu Shi
article en
4 citations

Abstract

Large Language Models (LLMs) are revolutionizing bioinformatics, enabling advanced analysis of DNA, RNA, proteins, and single-cell data.This survey provides a systematic review of recent advancements, focusing on genomic sequence modeling, RNA structure prediction, protein function inference, and single-cell transcriptomics.Meanwhile, we also discuss several key challenges, including data scarcity, computational complexity, and cross-omics integration, and explore future directions such as multimodal learning, hybrid AI models, and clinical applications.By offering a comprehensive perspective, this paper underscores the transformative potential of LLMs in driving innovations in bioinformatics and precision medicine.

Innovation and Technology Commission, Chinese University of Hong Kong
Openalex Percentile: Top 8%
Genetics, Bioinformatics, and Biomedical Research
3.22
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